Denedo tech SME / Architects, Databricks, Azure

Please focus on someone who knows the Denodo architecture, MPP systems, Caching and performance strategies and optimization with large volume of data. That is key.

the candidates should demonstrates the solid, hands-on expertise required to lead Denodo architecture. This includes practical experience with configuration and comfort with installations in Azure

Hope this works.

Job Summary :

Looking for a Data Architect with deep expertise in Denodo and MPP systems to lead performance optimization initiatives. The role requires diagnosing performance bottlenecks, optimizing caching strategies, and designing scalable architectures that minimize unnecessary compute and storage overhead. The ideal candidate will collaborate closely with data engineering and business teams to deliver impactful, cost-effective solutions.

Responsibilities

Lead architectural design and optimization for Denodo-based data virtualization platforms.

Analyze performance issues and formulate caching strategies to reduce cost and latency.

Evaluate and integrate MPP database solutions for high-performance querying.

Guide internal teams on Denodo best practices and governance.

Deliver roadmap for architectural transformation aligned to business SLAs and cost targets.

Qualifications

10+ years in data architecture with 5+ years in Denodo or similar data virtualization platforms.

Proven experience in tuning high-volume virtual queries and designing federated architectures.

Strong background in MPP databases like Snowflake, Redshift, Synapse, or BigQuery.

Expertise in data modeling, semantic layer optimization, and query pushdown strategies.

Strong client engagement and leadership experience with cross-functional teams.

Certifications

Denodo Certified Architect (strongly preferred).

Certification in any major MPP platform (e.g., Snowflake SnowPro, AWS Big Data Specialty).

TOGAF or other enterprise architecture certifications are a plus.

Bachelor's or Master's degree in Computer Science, Engineering, or related field.

Skills

Advanced SQL, query optimization, and virtual data modeling.

In-depth knowledge of data caching layers, indexing, and cost-based query planning.

Experience with cloud-native data architectures (AWS, Azure, or GCP).

Strong documentation, communication, and stakeholder management.

Performance benchmarking tools and observability platforms integration.